Street lights are important assets in a city's infrastructure. They provide safe roads in wide public areas and enhance security in homes, businesses and city centers. However, they are usually rather costly to operate. One of the reasons of the high costs is their energy consumption, which can be up to 40 percent of a cities electricity spending. Furthermore, usually street lights have to be inspected periodically to ensure maximum uptimes for safety and security. This, in addition to the electricity costs, causes significant cost of operation.
While street light manufacturers have enhanced their technology to increase both energy efficiency and operational reliability on a single street light basis, most issues in those terms regarding the overall network of street lights or rather street light systems operated by a city have not yet been addressed in a satisfying manner.
Addressing operation costs of a street light network of a city on a network level means managing the maintenance of the street lights not on the basis of single street lights but on the basis of the reliability of the network as a whole. Similarly, managing of the operation costs and in particular the electricity consumption of the street lights on a network basis means dimming lights, for example a number of street lights, to create a suitable light density in specific zones in accordance with schedules based on traffic volumes, once-off events, specific locations, public holidays and weekends, for quiet periods, and the like.
While applying such schemes can be useful in terms of saving energy in one of the largest energy consuming applications of city management, a tradeoff has to be judged with security embodiments. Therefore, while applying dimming and switching schemes to larger parts of the street light system with the aim of reducing electricity consumption in some parts of that same system, at the same time it may be adequate to use a higher level of light density to increase security as, for example, in dimly lit areas or areas generally known to be part of rather insecure neighborhoods.
The prerequisite for applying such asymmetric schemes of managing a street light maintenance and/or switching and dimming schemes of street lights is a reliable “knowledge” of the position of every street light relative to the geography of the respective city. Even though street lights are always typically fixed, of course, and their position is usually defined at installation time, the number of lamps already in a midsized city is large enough that alternative methods to detect any position of a single street light can be very useful, in particular because any software managing the above features of street light network management would need the positions of any lamp and further characteristics such as individual electricity consumption, light density, and the like on a real time basis, and in a digital format in order to apply and execute appropriate managing rules.
Therefore, there is a need for improved methods and systems for detecting street light position in large systems of street lights, such as systems in inner cities.